So sánh phương pháp

	Mô hình hiệu ứng cố định với dữ liệu bảng	Phương pháp Biến Công cụ (IV) cho Suy luận Nhân quả
Lĩnh vực	Kinh tế lượng	Kinh tế học y tế
Họ	Regression model	Process / pipeline
Năm ra đời	2005	1990s (modern applications)
Người khởi xướng	Baltagi (textbook treatment); Hausman test for FE vs RE choice	Angrist & Pischke (applied econometrics); rooted in econometric theory
Loại	Panel data regression	Method
Công trình gốc	Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251–1271.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Tên gọi khác	within estimator, panel fixed effects, entity fixed effects model, Panel Sabit Etkiler Modeli	IV, two-stage least squares, TSLS, causal estimation
Liên quan	5	3
Tóm tắt	The fixed effects panel model estimates relationships in panel data (many units observed over time) by exploiting only the within-unit variation, so that unobserved time-invariant heterogeneity is controlled away. It is the central within estimator developed in Baltagi's Econometric Analysis of Panel Data (2005), and the choice between it and the random effects model is settled by the Hausman (1978) test.	Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes.